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JMIETI, RADAUR
Lesson Plan of Mobile Application Development, Department-CSE, Semester8th,w.e.f January
Name of Teacher : Vishal GargDesignation : Assistant ProfessorSubject with code : Mobile Application Development (CSE-404)
Month Class Topic/Chapter Covered AcademicActivity
Test/Assignment
JAN L1 B.Tech 8thsem Mobility landscape, Lecture
Assignment from 1st Unit Tutorial sheet1 (based on previous question papers and important topics)
L2 B.Tech 8thsem Mobile platforms LectureL3 B.Tech 8thsem Mobile apps, Lecture
L4 B.Tech 8thsem Mobile apps Development LectureL5 B.Tech 8thsem Overview of android platform LectureL6 B.Tech 8thsem Setting up the Mobile app development Lecture
L7 B.Tech 8thsem environment along with an Emulator LectureL8 B.Tech 8thsem Activity –States and life Cycle LectureL9 B.Tech 8thsem L8 Continue... LectureL10 B.Tech 8thsem Interaction among the activities. Lecture
FEBL11 B.Tech 8thsem L10 Continue... Lecture Assignment from 2nd Unit Tutorial sheet1 (based on previous question papers and important topics)
L12 B.Tech 8thsem App functionality beyond user interface Lecture
L13 B.Tech 8thsem Revision LectureL14 B.Tech 8thsem Threads, Async task, LectureL 15 B.Tech 8thsem Task Services LectureL 16 B.Tech 8thsem States and life cycle LectureL17 B.Tech 8thsem Different States and life cycle Lecture
MARCHL 18
B.Tech 8thsem Notifications, broadcast receivers LectureAssignment from 3rd Unit Tutorial sheet1 (based on previous question papers and important topics)
L 19 B.Tech 8thsem broadcast receivers LectureL 20 B.Tech 8thsem Content provider LectureL 21 B.Tech 8thsem Continue... LectureL 22 B.Tech 8thsem Graphics and animation Custom views LectureL23 B.Tech 8thsem Custom views LectureL24 B.Tech 8thsem Canvas, animation APIs LectureL25 B.Tech 8thsem APIs Lecture
L 26 B.Tech 8thsem Multimedia Audio/Video playback andRecord
Lecture
Assignment from 4th UnitTutorial
L 27 B.Tech 8thsem Revision Lecture
L 28 B.Tech 8thsem Location awareness Lecture
L29 B.Tech 8thsem Native data handling file I/O LectureL30 B.Tech 8thsem L29 Continue... LectureL31 B.Tech 8thsem Different Native data handling file I/O Lecture
sheet1 (based on previous question papers and important topics)
L32 B.Tech 8thsem Shared preferences LectureL33 B.Tech 8thsem Shared preferences in detail LectureL34 B.Tech 8thsem Mobile databases such as SQLite Lecture
APRIL
L35 B.Tech 8thsem Enterprise data access ( via internet/intranet )
Lecture
L36 B.Tech 8thsem EDA Lecture
L37 B.Tech 8thsem Debugging mobile apps LectureL38 B.Tech 8thsem Detailed Debugging mobile apps LectureL39 B.Tech 8thsem White box testing Lecture
3rd SessionalL40 B.Tech 8thsem Black box testing LectureL41 B.Tech 8thsem Test automation of mobile app LectureL42 B.Tech 8thsem JUnit for Android Lecture
Course Outcomes (CO)1) Be exposed to technology and Mobile apps development aspects.2) Be competent with the characterization and architecture of mobile applications.3) Appreciation of nuances such as native hardware play, location awareness, graphics, and multimedia.4) Perform testing, signing, packaging and distribution of mobile apps.
JMIETI, Radaur Lesson Plan of Software Testing DepttCSE Semester 8th Semester
Name of Teacher : Tajinder Kumar
Designation : Assistant Professor
Subject with code : Software Testing Objective of Course: To provide an understanding of concepts and techniques for testing software and assuring its quality.Week & Month Topic / Chapter Covered Academic
ActivityTest/
AssignmentJANUARY L1 Overview of software evolution LECTUREL2 SDLC, Testing Process LECTUREL3 Terminologies in Testing: Error, Fault, Failure,
Verification, ValidationLECTURE
L4 Difference between Verification and Validation LECTUREL5 What is software testing and why it is so hard? LECTUREL6 Test Cases, Test Oracles, Testing Process LECTURE Assignment 1
L7 Limitations of Testing LECTUREL8 Functional Testing LECTUREL9 Boundary Value Analysis LECTUREL10 Equivalence Class Testing LECTUREL11 Decision Table Based Testing LECTUREFEBRUARYL12
Cause Effect Graphing Technique LECTURE
L13 Structural Testing LECTUREL14 Path testing LECTUREL15 DD-Paths LECTUREL 16 Cyclomatic Complexity LECTURE Assignment 2L 17 Graph Metrics LECTURE 1st sessionalL 18 Data Flow Testing, Mutation testing LECTUREL 19 Reducing the number of test cases LECTURE Assignment 3L20 Prioritization guidelines LECTUREL 21 Priority category, Scheme LECTURE Class Test 1
L 22 Risk Analysis, Regression Testing LECTUREMARCHL 24
Slice based testing LECTURE
L 25 Testing Activities LECTUREL26 Unit Testing LECTUREL 27 Levels of Testing LECTUREL 28 Integration Testing, System Testing LECTURE Class Test 2L29 Debugging, DomainTesting LECTURE
L30 Object oriented Testing: Definition, Issues LECTUREL 31 Class Testing LECTURE 2nd sessional
L 32 Object Oriented Integration and System Testing LECTURE
L33 Testing Web Applications: What is Web testing? LECTUREL34 User interface Testing LECTUREL35 Usability Testing, Security Testing LECTURE Assignment 4L36 procedure of manual testing LECTUREApril L37 difference between a Standalone application,
Client-Server application and Web application
LECTURE
L38 Compatibility Testing, Usability Testing,Security Testing and Soak Testing.
LECTURE
L39 Globalization Testing,Localization Testing,Installation Testing,
LECTURE 3rd Sessional
L40 Exploratory Testing,Monkey Testing LECTUREL41 Formal Testing,Risk Based Testing LECTURE
Outcome of Course:1) Expose the criteria and parameters for the generation of test cases.2) Learn the design of test cases and generating test cases3) Be familiar with test management and software testing activities4) Be exposed to the significance of software testing in web and Object orient techniques.
JMIETI,RADAURLesson Planning of Neural Network Deptt CSE 8th Semester w.e.f 06/01/2020
Name of Teacher : RohitBathla
Designation : Assistant Professor
Subject with code : Neural NetworkObjective:
Month Class Topic/Chapter Covered AcademicActivity
Test/Assignment
JANUARYL1
B.Tech 8thsem Introduction : Concepts of neural networks Lecture
Assignment from 1st Unit Tute sheet1 (based on previous question papers and important topics)
L2 B.Tech 8thsem Basics of neural networks Lecture
L3 B.Tech 8thsem Characteristics of neural networks Lecture
L4 B.Tech 8thsem L3 Continue...... Lecture
L5 B.Tech 8thsem Applications of neural networks Lecture
L6 B.Tech 8thsem L5 Continue.... Lecture
L7 B.Tech 8thsem Fundamentals of neural networks Lecture
L8 B.Tech 8thsem Details of Fundamentals of neural networks
Lecture
L9 B.Tech 8thsem What do you mean by Prototype Lecture
L10 B.Tech 8thsem The biological prototype Lecture
L11 B.Tech 8thsem Neuron concept , Lecture
FEBRUARYL12
B.Tech 8thsem single layer neural networks Lecture Assignment from 2nd Unit Tute sheet1 (based on previous question papers and important topics)
L13 B.Tech 8thsem Multi-Layer neural networks. Lecture
L14 B.Tech 8thsem Terminology Lecture
L15 B.Tech 8thsem Notation of neural networks Lecture
L 16 B.Tech 8thsem representation of neural networks Lecture
L 17 B.Tech 8thsem Training of artificial neural networks Lecture
L 18 B.Tech 8thsem L17 Continue.... Lecture
L 19 B.Tech 8thsem Representations of perceptron, Lecture
L20 B.Tech 8thsem L20 Continue.... Lecture
L 21 B.Tech 8thsem perceptron learning and training Lecture
L 22 B.Tech 8thsem Perceptrontraining Lecture
M
MARCHL 24
B.Tech 8thsem Classification , linear separability Lecture
Assignment from 3rd Unit Tute sheet1 (based on previous question papers and important topics)
L 25 B.Tech 8thsem linear separability Lecture
L26 B.Tech 8thsem Hopfield nets: Structure, Lecture
L 27 B.Tech 8thsem Structure, Lecture
L 28 B.Tech 8thsem Training Lecture
L29 B.Tech 8thsem applications, Lecture
L30 B.Tech 8thsem Back propagation : concept, applications Lecture
L 31 B.Tech 8thsem Back propagation Training algorithms. Lecture
L 32 B.Tech 8thsem Counter propagation Networks: kohonanNetwork
Lecture
L33 B.Tech 8thsem gross berg layer &Training Lecture
L34 B.Tech 8thsem Applications of counter propagation. Lecture
L35 B.Tech 8thsem Image classification. Lecture
L 36 B.Tech 8thsem Bi-directional associative memories Lecture
Assignment from 4th UnitTute sheet1 (based on previous question papers and
L 37B.Tech 8thsem L34 Continue... Lecture
L 38 B.Tech 8thsem Structure, retrieving a stored association, Lecture
L 39 B.Tech 8thsem encoding associations Lecture
L40 B.Tech 8thsem Art architecture Lecture
L41 B.Tech 8thsem Art Classification operation, Lecture
L42 B.Tech 8thsem ART implementation Lecture
L43 B.Tech 8thsem characteristics of ART Lecture
L44 B.Tech 8thsem Image compression using art , Lecture
APRILL45
B.Tech 8thsem optical neural networks , Lecture
L46 B.Tech 8thsem Vector Matrix multipliers Lecture
L 47 B.Tech 8thsem Hop field net using Electro optical matrixmultipliers,
Lecture
important topics)
L 48 B.Tech 8thsem holographic correlator, Lecture
L 49 B.Tech 8thsem Optical Hopfield net suing volume holograms,
Lecture
L 50 B.Tech 8thsem cognitrons and neocognitrons: Structure Lecture
and training
L 51 B.Tech 8thsem Fuzzy Logic :introduction of fuzzy logic,Classical and fuzzy sets
Lecture
L52 B.Tech 8thsem Overview of classical sets, membershipFunction, Fuzzy rule generation,
Lecture
L53 B.Tech 8thsem Operations on Fuzzy sets: compliment , Lecture
L54 B.Tech 8thsem intersections, Unions, combinations of operations,
Lecture
L55 B.Tech 8thsem Aggregation Operations, Fuzzy Arithmetic: Fuzzy Numbers, Linguistic variables,
Lecture
L56 B.Tech 8thsem Arithmetic Operations on Intervals & Numbers,
Lecture
L57 B.Tech 8thsem Lattice of Fuzzy Numbers, Fuzzy Equations
Lecture
L58 B.Tech 8thsem Introduction of Neruo Fuzzy systems architecture of Neuro Fuzzy networks
Lecture
L59 B.Tech 8thsem Genetic Algorithms: genetic algorithmimplementation in problem solving and
Lecture
L60 B.Tech 8thsem Working of genetic algorithms evolvingneural networks
Lecture
JMIETI, RadaurLesson Planning of Parallel Computing Deptt. CSE Semester 8th
Name of Teacher : Ms.Ruchi Gupta
Designation : Assistant Professor
Subject with code : Parallel Computing (CSE-418)
Objectives of Course :
1. Parallel Programming Platforms.
2. Principles of Parallel Algorithm Design.
3. Analytical Modeling of Parallel Programs.
4. Parallel Programming Paradigms.Month Topic /chapter
covered Academic activity Test / assignment
JAN Introduction: The state of computing, system attributes to performance
Teaching
JAN Paradigms of parallel computing: Synchronous – Vector/ Array, SIMD, systolic
Teaching
JAN Asynchronous- MIMD, reduction paradigm.
Teaching
JAN Hardware Taxonomy: Flynn’s classification
Teaching
JAN Feng’s classification, handler’s classification
Teaching
JAN Software taxonomy: Kung’s taxonomy TeachingJAN TestFEB Abstract parallel computational models:
combinational circuits, sorting networkTeaching
FEB PRAM models, VLSI complexity model, Interconnections RAMs
Teaching
FEB Parallelism approaches- data parallelism, control parallelism,
Teaching
FEB Conditions of parallelism: Data, control and resource dependencies
Teaching
FEB Hardware and software parallelism. TeachingFEB Performance metrics: Laws governing
performance measurementsTeaching
FEB Metrics- speedups, efficiency, utilization, communication overheads, single/ multiple program performances.
Teaching
FEB TestMAR Parallel processors: taxonomy and
topology: shared memory multi processorsTeaching
MAR Distributed memory multicomputer, static and dynamic interconnections.
Teaching
MAR Parallel programming: shared memory Teaching
programming, distributed memory programming
MAR Object oriented programming, TeachingMAR Data parallel programming TeachingMAR Distributed memory programming TeachingMAR Functional programming TeachingMAR Data flow programming TeachingMAR TestAPR Scheduling and parallelization: Loop
parallelization and pipeliningTeaching
APR Loop transformation theory,parallelization and wave fronting,
Teaching
APR Tiling and localization, TeachingAPR Software pipelining, TeachingAPR Scheduling parallel programs, program
partitioning and scheduling:Teaching
APR Grain size, latency, grain packing and scheduling
Teaching
APR Loop scheduling, Parallelization of sequential programs
Teaching
APR Test
Outcomes of Course:1. Classify various synchronous and asynchronous paradigms of parallel computing as well as
identify some of the taxonomies for architectural classification of parallel computers.2. Compare various parallel computation models and approaches and describe different
performance metrics in parallel computers. 3. Distinguish shared memory and distributed memory multiprocessors and explainvarious
parallel programming models and relative advantages and disadvantages of interconnection networks based on network parameters for reliable connections and achieving efficient speed.
4. Examine various techniques of parallelizing loops and sequential programs and scheduling.
(Sign. of HOD) (Sign. of Teacher Concerned with date)